Critical Metadata Protocols in Hyperspectral Field Campaigns for Building Robust Hyperspectral Datasets

Rasaiah, Barbara A.; Jones, Simon; Malthus, Tim J.; Bellman, Chris

doi:10.5194/isprsarchives-xxxix-b2-161-2012

Cited by 6 publications

(2 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Interoperability of field spectroscopy metadata is central to facilitating common platforms for sharing field spectroscopy datasets within the remote sensing community [1][2][3][4][5][6]. A field spectroscopy metadata standard is defined as those data elements that explicitly document the spectroscopy dataset and field protocols, sampling strategies, instrument properties and environmental and logistical variables [5].…”

Section: The Importance Of Interoperable Field Spectroscopy Metadatasetsmentioning

confidence: 99%

Towards an Interoperable Field Spectroscopy Metadata Standard with Extended Support for Marine Specific Applications

et al. 2015

View full text Add to dashboard Cite

This paper presents an approach to developing robust metadata standards for specific applications that serves to ensure a high level of reliability and interoperability for a spectroscopy dataset. The challenges of designing a metadata standard that meets the unique requirements of specific user communities are examined, including in situ measurement of reflectance underwater, using coral as a case in point. Metadata schema mappings from seven existing metadata standards demonstrate that they consistently fail to meet the needs of field spectroscopy scientists for general and specific applications (μ = 22%, σ = 32% conformance with the core metadata requirements and μ = 19%, σ = 18% for the special case of a benthic (e.g., coral) reflectance metadataset). Issues such as field measurement methods, instrument calibration, and data representativeness for marine field spectroscopy campaigns are investigated within the context of submerged benthic measurements. The implication of semantics and syntax for a robust and flexible metadata standard are also considered. A hybrid standard that serves as a "best of breed" incorporating useful modules and parameters within the standards is proposed. This paper is Part 3 in a series of papers in this journal, examining the issues central to a metadata standard for field spectroscopy datasets. The results presented in this paper are an important step towards field spectroscopy metadata standards that address the specific needs of field OPEN ACCESSRemote Sens. 2015, 7 15669 spectroscopy data stakeholders while facilitating dataset documentation, quality assurance, discoverability and data exchange within large-scale information sharing platforms.

show abstract

Section: The Importance Of Interoperable Field Spectroscopy Metadatasetsmentioning

confidence: 99%

Towards an Interoperable Field Spectroscopy Metadata Standard with Extended Support for Marine Specific Applications

et al. 2015

View full text Add to dashboard Cite

show abstract

“…There is no standardized methodology for documentation of field spectroscopy data or metadata [1][2][3][4][5]. The need for a standardized methodology for collecting-and assuring the quality of-field spectroscopy metadata has increased with the emergence of data sharing initiatives such as NASA's EOSDIS (Earth Science Data and Information System), the LTER (Long Term Ecological Research) network, the Australian Terrestrial Ecosystem Research Network (TERN), SpecNet [6] and some of the smaller ad hoc spectral libraries and databases created by remote sensing communities internationally.…”

Section: The Importance Of Field Spectroscopy Metadatamentioning

confidence: 99%

Assessing Field Spectroscopy Metadata Quality

et al. 2015

View full text Add to dashboard Cite

This paper presents the proposed criteria for measuring the quality and completeness of field spectroscopy metadata in a spectral archive. Definitions for metadata quality and completeness for field spectroscopy datasets are introduced. Unique methods for measuring quality and completeness of metadata to meet the requirements of field spectroscopy datasets are presented. Field spectroscopy metadata quality can be defined in terms of (but is not limited to) logical consistency, lineage, semantic and syntactic error rates, compliance with a quality standard, quality assurance by a recognized authority, and reputational authority of the data owners/data creators. Two spectral libraries are examined as case studies of operationalized metadata policies, and the degree to which they are aligned with the needs of field spectroscopy scientists. The case studies reveal that the metadata in publicly available spectral datasets are underperforming on the quality and completeness measures. This paper is part two in a series examining the issues central to a metadata standard for field spectroscopy datasets.

show abstract

Spectral matching approaches in hyperspectral image processing

Sanjeevi

SrinivasaPerumal

2014

International Journal of Remote Sensing

View full text Add to dashboard Cite

Many spectral matching algorithms, ranging from the traditional clustering techniques to the recent automated matching models, have evolved. This paper provides a review and up-to-date information on the past and current role of the spectral matching approaches adopted in hyperspectral satellite image processing. The need for spectral matching has been deliberated and a list of spectral matching algorithms has been compared and described. A review of the conventional spectral angle measures and the advanced automated spectral matching tools indicates that, for better performance of target detection, there is a need for combining two or more spectral matching techniques. From the studies of several authors, it is inferred that continuous improvement in the matching techniques over the past few years is due to the need to handle and analyse hyperspectral image data for various applications. The need to develop a wellbuilt and specialized spectral library to accommodate the resources from enormous spectral data is suggested. This may improve accuracy in mineral and soil mapping, vegetation species identification and health monitoring, and target detection. The future role of cloud computing in accessing globally distributed spectral libraries and performing spectral matching is highlighted. Rather than inferring that a particular matching algorithm is the best, this paper points out the requirements of an ideal algorithm. With increasing usage of hyperspectral data for resources mapping, the review presented in this paper will certainly benefit the large and emerging community of hyperspectral image users.

show abstract

Critical Metadata Protocols in Hyperspectral Field Campaigns for Building Robust Hyperspectral Datasets

Cited by 6 publications

References 2 publications

Towards an Interoperable Field Spectroscopy Metadata Standard with Extended Support for Marine Specific Applications

Towards an Interoperable Field Spectroscopy Metadata Standard with Extended Support for Marine Specific Applications

Assessing Field Spectroscopy Metadata Quality

Spectral matching approaches in hyperspectral image processing

Contact Info

Product

Resources

About